Lead: On 24 February 2026, The Guardian podcast hosted by Ian Sample explored how body fat is far from inert, describing it as an active, communicative tissue that affects metabolism and cardiovascular health. Guests included co-host Madeleine Finlay and Declan O’Regan, professor of cardiovascular AI at Imperial College London, who discussed new imaging and computational work linking fat distribution to disease risk. The episode highlights a shift in scientific thinking: many researchers now treat adipose tissue as an endocrine, immune and metabolic actor — sometimes described as an organ in its own right. The conversation outlined both established roles for fat and the open questions researchers are racing to answer.
Key takeaways
- Fat is biologically active: adipose tissue secretes hormones and signalling molecules (adipokines) that influence appetite, inflammation and insulin sensitivity.
- Types of fat matter: white, brown and beige adipose tissues have distinct cellular functions — brown fat is specialised for heat production while white stores energy.
- Location matters for risk: visceral fat around organs is more strongly associated with cardiometabolic disease than subcutaneous fat beneath the skin.
- Some scientists now call fat an organ: that framing reflects its endocrine, immune and metabolic roles, though consensus on terminology is not universal.
- Imaging plus AI is advancing insight: Declan O’Regan and colleagues use cardiovascular imaging and machine learning to map fat distribution and link patterns to heart disease risk.
- Clinical translation is ongoing: researchers are testing ways to target fat function (not just amount), but proven therapies that reprogram adipose tissue remain limited.
- Public health context persists: rising global overweight and obesity rates amplify interest in fat biology as a lever for preventing diabetes and heart disease.
Background
For decades popular and medical narratives treated fat primarily as stored energy and a cosmetic issue. That view emphasised calories in versus calories out and focused on body weight as the main clinical metric. Over the past two decades, however, molecular and physiological studies revealed that adipose tissue releases signalling molecules — leptin, adiponectin and others — that change appetite, inflammation and insulin sensitivity, prompting researchers to reconsider its functional importance.
Parallel advances in imaging, histology and single-cell genomics have shown that adipose depots are heterogeneous: different fat pads contain distinct cell types and immune populations, and they change with age, diet and environment. These findings shifted debate from ‘how much fat’ to ‘what kind and where’, and they spurred interdisciplinary interest from endocrinology, immunology and cardiovascular medicine. Policymakers and clinicians increasingly view fat as central to metabolic disease pathways, not merely an inert risk marker.
Main event
In the podcast episode recorded for The Guardian, Ian Sample guided listeners through these developments with two guests: Madeleine Finlay, co-host, who framed the public-health and cultural dimensions, and Professor Declan O’Regan, who described how AI applied to cardiovascular scans is revealing clinically relevant patterns in fat distribution. The discussion opened with the idea that fat is ‘in conversation’ with other tissues — a shorthand for the endocrine and immune cross-talk now well documented in lab studies.
O’Regan outlined how cardiac and body imaging datasets, when analysed with machine-learning models, can detect subtle features of ectopic and visceral fat that predict heart disease beyond traditional risk factors. He emphasised that these tools are correlational at present: they flag risk patterns but do not by themselves prove causation. The hosts discussed potential clinical uses, such as refining risk stratification and tailoring preventative strategies based on where fat accumulates.
The episode also covered therapeutic directions under investigation: strategies range from drugs that modify adipose inflammation to behavioural interventions that change fat function, and laboratory work exploring ways to increase energy-burning brown fat. Throughout, guests stressed the gap between mechanistic insight and ready-to-use clinical interventions — translating cellular discoveries into safe, effective treatments will take time.
Analysis & implications
Reframing adipose tissue as an active participant in physiology has immediate implications for diagnosis and prevention. If clinicians begin to classify risk by fat distribution and function rather than by body-mass index alone, screening protocols may shift toward more imaging and biomarker assessment. That transition could improve individual risk prediction, but it also raises questions about cost, access and potential overmedicalisation of body differences.
For cardiology and metabolic medicine, the integration of imaging data with AI models promises stronger risk models that capture previously hidden features of fat. However, algorithmic models trained on imaging cohorts face challenges of representativeness: populations underrepresented in datasets may receive less accurate predictions. Ethical deployment will require transparent validation across diverse groups and careful regulatory oversight.
On the therapeutic front, distinguishing fat function from fat quantity opens new targets: modulating adipose inflammation or enhancing brown-fat activity could change disease trajectories without substantial weight loss. Yet most candidate interventions remain in early-stage trials or preclinical work. Policymakers must balance optimism about biological targets with the immediate need to address environmental and social drivers of excess adiposity at population scale.
Comparison & data
| Fat type | Primary function | Clinical relevance |
|---|---|---|
| White adipose | Energy storage, adipokine secretion | Associated with obesity-related insulin resistance |
| Brown adipose | Thermogenesis (heat production) | Potential target to increase energy expenditure |
| Beige adipose | Inducible thermogenic activity | Research target for metabolic therapies |
The table summarises broad functional differences that underpin current research priorities. Researchers emphasise heterogeneity: even within ‘white’ fat there are depot-specific differences (visceral vs subcutaneous) that correlate differently with metabolic risk. Imaging studies cited in the episode use cross-sectional and longitudinal scans to map these depot-level associations, while molecular studies investigate cell-type changes that accompany metabolic disease.
Reactions & quotes
“It’s now even considered by some to be an organ in its own right,”
The Guardian podcast (Ian Sample & Madeleine Finlay)
This phrase summarises a framing used in the episode to capture adipose tissue’s endocrine and immune roles. The hosts used it to explain why researchers are shifting away from treating fat as inert.
“Imaging and AI are revealing patterns of fat distribution linked to cardiac risk,”
Declan O’Regan, Professor of Cardiovascular AI, Imperial College London
O’Regan described how computational analysis of scans can identify fat-related patterns that add predictive value to established risk factors. He emphasised that these tools are currently complementary risk markers rather than definitive causal evidence.
Unconfirmed
- Whether adipose tissue should be formally classified as an organ by medical consensus — the term is used by some researchers but is not universally adopted.
- The extent to which modulating brown or beige fat will produce clinically meaningful weight loss or cardiovascular benefit in large human populations remains unproven.
- AI-derived imaging markers show associations with disease, but whether they improve outcomes when used in clinical decision-making has not been established.
Bottom line
The Guardian podcast episode underscores a substantive change in how science frames body fat: from passive storage to an active, signalling tissue with systemic effects. That reframing motivates new diagnostic approaches — especially imaging combined with AI — and fresh therapeutic targets focused on adipose function rather than weight alone. Listeners should recognise that while biological insight has advanced rapidly, translation into broadly effective clinical tools and population-level impact will take time and careful validation.
For patients and clinicians today, the practical takeaway is nuanced: fat quantity, type and location all contribute to health risk, and interventions may need to be tailored accordingly. Meanwhile, public-health strategies that address diet, activity and social determinants of health remain essential complements to biomedical research aimed at reprogramming adipose tissue.